Refactor player selection display in Handbuilder tab of app.py to utilize a dataframe for selected players, improving selection accuracy and user experience. Update summary row calculation to align with new selection method, ensuring accurate display of total salary, median, and ownership percentage.

app.py

@@ -802,20 +802,17 @@ with tab3:
 with tab4:
     st.header("Handbuilder")
 
-    # Use a variable to control the key
     if 'handbuilder_editor_key' not in st.session_state:
         st.session_state.handbuilder_editor_key = 0
 
     if st.button("Clear Data", key='clear_handbuild'):
-        st.session_state.handbuilder_editor_key += 1  # Change the key to force reset
-        # Reset all selections
-        st.session_state.handbuilder_editor_df = None
+        st.session_state.handbuilder_editor_key += 1
         st.rerun()
 
     # --- TEAM FILTER UI ---
     all_teams = sorted(dk_roo['Team'].unique())
     st.markdown("**Toggle teams to include:**")
-    team_cols = st.columns(len(all_teams) // 2 + 1)  # Spread switches across columns
+    team_cols = st.columns(len(all_teams) // 2 + 1)
 
     selected_teams = []
     for idx, team in enumerate(all_teams):
@@ -826,46 +823,27 @@ with tab4:
         if checked:
             selected_teams.append(team)
 
-    # --- PLAYER SELECTION STATE ---
-    # Initialize or update the session state DataFrame
-    if 'handbuilder_editor_df' not in st.session_state or st.session_state.handbuilder_editor_df is None:
-        # Start with all players, all unchecked
-        base_df = dk_roo[['Player', 'Position', 'Team', 'Salary', 'Median', 'Order', 'Hand', 'Own%']].copy()
-        base_df['Select'] = False
-        st.session_state.handbuilder_editor_df = base_df
-    else:
-        # Make sure all players are present (in case teams change)
-        base_df = st.session_state.handbuilder_editor_df
-
-    # Filter by selected teams (or all if none selected)
+    # If no teams selected, show all teams
     if selected_teams:
-        filtered_df = base_df[base_df['Team'].isin(selected_teams)].copy()
+        player_select_df = dk_roo[
+            dk_roo['Team'].isin(selected_teams)
+        ][['Player', 'Position', 'Team', 'Salary', 'Median', 'Order', 'Hand', 'Own%']].copy()
     else:
-        filtered_df = base_df.copy()
+        player_select_df = dk_roo[['Player', 'Position', 'Team', 'Salary', 'Median', 'Order', 'Hand', 'Own%']].copy()
 
     col1, col2 = st.columns([1, 2])
     with col2:
         st.subheader("Player Select")
-        edited_df = st.data_editor(
-            filtered_df,
-            column_config={
-                "Select": st.column_config.CheckboxColumn(
-                    "Select",
-                    help="Check to add player to lineup",
-                    default=False
-                )
-            },
-            use_container_width=True,
-            hide_index=True,
-            key=f"handbuilder_editor_{st.session_state.handbuilder_editor_key}"
+        event = st.dataframe(
+            player_select_df,
+            key=f"handbuilder_editor_{st.session_state.handbuilder_editor_key}",
+            on_select="rerun",
+            selection_mode=["multi-row"]
         )
-        # Update the session state DataFrame with the new selections
-        # (merge back into the full base_df)
-        st.session_state.handbuilder_editor_df.update(edited_df)
 
-    # Filter selected players for the lineup
-    selected_players = st.session_state.handbuilder_editor_df[st.session_state.handbuilder_editor_df['Select'] == True]
-    select_players_disp = selected_players[['Player', 'Team', 'Salary', 'Median', 'Own%']]
+    # Get selected rows
+    selected_indices = event.selection["rows"] if event and "rows" in event.selection else []
+    select_players_disp = player_select_df.iloc[selected_indices][['Player', 'Team', 'Salary', 'Median', 'Own%']]
 
     with col1:
         st.subheader("Lineup")
@@ -878,14 +856,11 @@ with tab4:
 
         # --- SUMMARY ROW ---
         if not select_players_disp.empty:
-            # Calculate sums
             total_salary = select_players_disp['Salary'].sum()
             total_median = select_players_disp['Median'].sum()
             total_own = select_players_disp['Own%'].sum()
-            # Most common team
             most_common_team = select_players_disp['Team'].mode()[0] if not select_players_disp['Team'].mode().empty else ""
 
-            # Create a summary row as a DataFrame
             summary_row = pd.DataFrame({
                 'Player': ['TOTAL'],
                 'Team': [most_common_team],
@@ -893,16 +868,11 @@ with tab4:
                 'Median': [total_median],
                 'Own%': [total_own]
             })
-
-            # Align columns with select_players_disp
             summary_row = summary_row[select_players_disp.columns]
 
-            # Display the summary row
             st.dataframe(
                 summary_row,
                 use_container_width=True,
                 height=50,
                 hide_index=True
-            )
-    
-    
+            )